standards > reporting guideline > DOI:10.25504/FAIRsharing.8ntfwm

ready Standards for Reporting Enzymology Data Guidelines

Abbreviation: STRENDA

General Information
STRENDA stands for “Standards for Reporting Enzymology Data”. For researchers it is essential to be able to compare, evaluate, interpret and reproduce experimental research results published in the literature and databases. Thus, for enzyme research, the STRENDA Commission has established standards for data reporting with the aim to improve the quality of data published in the scientific literature. The STRENDA Guidelines were developed through extensive interactions with the biochemistry community to define the minimum information that is needed to correctly describe assay conditions (List Level 1A) and enzyme activity data (List Level 1B). However, STRENDA aims neither to dictate or limit the experimental techniques used in enzymology experiments nor to establish a metric for judging the quality of experimental data, but to ensure that data sets are complete and validated, allowing scientists to review, reuse and verify them. The emphasis is on providing useful and reliable information. Recommending Journals With the aim to support authors to comprehensively report kinetic and equilibrium data from their investigations of enzyme activities, currently more than 30 international biochemistry journals already included the STRENDA Guidelines in their Instructions for Authors.

How to cite this record STRENDA; Standards for Reporting Enzymology Data Guidelines; DOI:; Last edited: Jan. 8, 2019, 1:32 p.m.; Last accessed: Jan 27 2020 6:26 a.m.

This record is maintained by CKettner  ORCID

Record updated: Nov. 14, 2018, 1:36 p.m. by The FAIRsharing Team.

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The importance of uniformity in reporting protein-function data.

Apweiler R, Cornish-Bowden A, Hofmeyr JH, Kettner C, Leyh TS, Schomburg D, Tipton K
Trends Biochem Sci 2005

View Paper (PubMed) View Publication

A large-scale protein-function database

Apweiler R, Armstrong R, Bairoch A, Cornish-Bowden A, Halling PJ, Hofmeyr JH, Kettner C, Leyh TS, Rohwer J, Schomburg D, Steinbeck C, Tipton K.
Nat Chem Biol. 2010

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Standards for Reporting Enzyme Data: The STRENDA Consortium: What it aims to do and why it should be helpful

Keith F. Tipton, Richard N. Armstrong, Barbara M. Bakker, Amos Bairoch, Athel Cornish-Bowden, Peter J. Halling, Jan-Hendrik Hofmeyr, Thomas S. Leyh, Carsten Kettner, Frank M. Raushel, Johann Rohwer, Dietmar Schomburg, Christoph Steinbeck
Perspectives in Science 2014

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Implementing Databases (1)
STRENDA DB is a storage and search platform supported by the Beilstein-Institut that incorporates the STRENDA Guidelines in a user-friendly, web-based system. If you are an author who is preparing a manuscript containing functional enzymology data, STRENDA DB provides you the means to ensure that your data sets are complete and valid before you submit them as part of a publication to a journal. Data entered in the STRENDA DB submission form are automatically checked for compliance with the STRENDA Guidelines; users receive warnings informing them when necessary information is missing. A successful formal compliance is confirmed by the awarding of a STRENDA Registry Number (SRN) and documented in a fact sheet (PDF) containing all input data that can be submitted with the manuscript to the journal. In addition, each dataset is assigned a DOI that allows reference and tracking of the data. The data become publicly available in the database only after the corresponding article has been peer-reviewed and published in a journal. The STRENDA Commission, comprising an international panel of highly-regarded scientists who have wide-ranging expertise in areas such as biochemistry, enzyme nomenclature, bioinformatics, systems biology, modelling, mechanistic enzymology and theoretical biology, has established standards for data reporting in enzymology research. The aim of these STRENDA Guidelines is to improve the quality of data published in the scientific literature and to enable researchers to compare, evaluate, interpret and reproduce experimental research results published in the literature and databases.


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